Traditional acoustic echo cancellation (AEC) works by identifying an acoustic impulse
response using adaptive algorithms. This paper proposes a neural cascade architecture for …

In this contribution, we introduce a novel approach to noise-robust acoustic echo
cancellation employing a complex-valued Deep Neural Network (DNN) for postfiltering. In a …

This paper presents a real-time Acoustic Echo Cancellation (AEC) algorithm submitted to the
AEC-Challenge. The algorithm consists of three modules: Generalized Cross-Correlation …

Deep-leaming based acoustic echo cancellation (AEC) methods have been shown to
outperform the classical techniques. The main drawback of the learning-based AEC is its …

In recent years, deep neural networks (DNNs) were studied as an alternative to traditional
acoustic echo cancellation (AEC) algorithms. The proposed models achieved remarkable …

In this paper, we propose a residual echo suppression method using a UNet neural network
that directly maps the outputs of a linear acoustic echo canceler to the desired signal in the …

Traditional stereophonic acoustic echo cancellation algorithms need to estimate acoustic
echo paths from stereo loudspeakers to a microphone, which often suffers from the …

This paper proposes the Cross-Domain Echo-Controller (CDEC), submitted to the
Interspeech 2021 AEC-Challenge. The algorithm consists of three building blocks:(i) a Time …

Acoustic echo cancellation (AEC) algorithms have a long-term steady role in signal
processing, with approaches improving the performance of applications such as automotive …

In this paper, we propose a neural cascade architecture for joint acoustic echo and noise
suppression. The proposed cascade architecture consists of two modules. A convolutional …